Cited by 143Complex Network Analysis TechniquesSocial Capital and NetworksGame Theory and Applications

Gossip: Identifying Central Individuals in a Social Network

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Banerjee, Abhijit, Chandrasekhar, Arun, Duflo, Esther, Jackson, Matthew·2014·National Bureau of Economic Research

Abstract

Abstract. Can we identify the members of a community who are best-placed to diffuse information simply by asking a random sample of in-dividuals? We show that boundedly-rational individuals can, simply by tracking sources of gossip, identify those who are most central in a network according to “diffusion centrality, ” which nests other standard centrality measures. Testing this prediction with data from 35 Indian villages, we find that respondents accurately nominate those who are diffusion central (not just those with many friends). Moreover, these nominees are more central in the network than traditional village leaders and geographically central individuals.

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  • Highly connected individuals possess outsized influence, and it is unlikely that their centrality is solely related to being a producer of higher-quality information.

    “Highly connected individuals possess outsized influence, and it is unlikely that their centrality is solely related to being a producer of higher-quality information”

    From Stewardship of global collective behavior (2021) · cites this paper as [85]

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Research works printed but not linked: 1

  1. Ambrus, A., M. Mobius, and A. Szeidl (2014): 'Consumption RiskSharing in Social Networks,' American Economic Review , 104, 149-82. 5.2

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Authors
Banerjee, A., Chandrasekhar, A., Duflo, E., & Jackson, M.
Affiliations
Santa Fe Institute (US)
Venue
National Bureau of Economic Research
Published
2014-08
OpenAlex
W2168342758
Cited by
143
References
32
Citations by year
2026: 1 · 2025: 6 · 2024: 7 · 2023: 5 · 2022: 5 · 2021: 10 · 2020: 15 · 2019: 17 · 2018: 16 · 2017: 17 · 2016: 16 · 2015: 18 · 2014: 8 · 2012: 2
Type
report
Language
en
Open access
Locations
  • National Bureau of Economic Research (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • National Bureau of Economic Research (submittedVersion)
Topics
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
  • Social Sciences › Sociology and Political Science › Social Capital and Networks
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Game Theory and Applications
Keywords
gossip, social network centrality, information dissemination, community leaders, social influence, Indian villages

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